{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# How to recover a known planet in Kepler data?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This tutorial demonstrates the basic steps required to recover a transiting planet candidate in the Kepler data.\n", "\n", "We will show how you can recover the signal of [Kepler-10b](https://en.wikipedia.org/wiki/Kepler-10b), the first rocky planet that was discovered by Kepler! Kepler-10 is a Sun-like (G-type) star approximately 600 light years away in the constellation of Cygnus. In this tutorial, we will download the pixel data of Kepler-10, extract a lightcurve, and recover the planet." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Kepler pixel data is distributed in \"Target Pixel Files\". You can read more about them in our tutorial [here](http://lightkurve.keplerscience.org/tutorials/target-pixel-files.html). The `lightkurve` package provides a `KeplerTargetPixelFile` class, which enables you to load and interact with data in this format.\n", "\n", "The class can take a path (local or url), or you can load data straight from the [MAST archive](https://archive.stsci.edu/kepler/), which holds all of the Kepler and K2 data archive. We'll download the Kepler-10 light curve using the `from_archive` function, as shown below. *(Note: we're adding the keyword `quarter=3` to download only the data from the third Kepler quarter. There were 17 quarters during the Kepler mission.)*" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Downloading URL https://mast.stsci.edu/api/v0/download/file?uri=mast:Kepler/url/missions/kepler/target_pixel_files/0119/011904151/kplr011904151-2009350155506_lpd-targ.fits.gz to ./mastDownload/Kepler/kplr011904151_lc_Q111111110111011101/kplr011904151-2009350155506_lpd-targ.fits.gz ... [Done]\n" ] } ], "source": [ "from lightkurve import KeplerTargetPixelFile\n", "tpf = KeplerTargetPixelFile.from_archive(\"Kepler-10\", quarter=3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's use the `plot` method and pass along an aperture mask and a few plotting arguments." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "tpf.plot(scale='log');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The target pixel file contains one bright star with approximately 50,000 counts." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, we will use the ``to_lightcurve`` method to create a simple aperture photometry lightcurve using the\n", "mask defined by the pipeline which is stored in `tpf.pipeline_mask`." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "lc = tpf.to_lightcurve(aperture_mask=tpf.pipeline_mask)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's take a look at the output lightcurve." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "lc.plot();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's use the `flatten` method, which applies a Savitzky-Golay filter, to remove long-term variability that we are not interested in. We'll use the `return_trend` keyword so that it returns both the corrected `KeplerLightCurve` object and a new `KeplerLightCurve` object called 'trend'. This contains only the long term variability." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [], "source": [ "flat, trend = lc.flatten(window_length=301, return_trend=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's plot the trend estimated by the Savitzky-Golay filter:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax = lc.plot() #plot() returns a matplotlib axis \n", "trend.plot(ax, color='red'); #which we can pass to the next plot() to use the same plotting window" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "and the flat lightcurve:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "flat.plot();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, let's run a period search function using the Box-Least Squares algorithm (http://adsabs.harvard.edu/abs/2002A%26A...391..369K). We will shortly have a built in BLS implementation, but until then you can download and install it separately from lightkurve using" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`pip install git+https://github.com/mirca/transit-periodogram.git`" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from transit_periodogram import transit_periodogram\n", "import numpy as np\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": true }, "outputs": [], "source": [ "periods = np.arange(0.3, 1.5, 0.0001)\n", "durations = np.arange(0.005, 0.15, 0.001)\n", "power, _, _, _, _, _, _ = transit_periodogram(time=flat.time, \n", " flux=flat.flux,\n", " flux_err=flat.flux_err,\n", " periods=periods, \n", " durations=durations)\n", "best_fit = periods[np.argmax(power)]" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best Fit Period: 0.8375999999999408 days\n" ] } ], "source": [ "print('Best Fit Period: {} days'.format(best_fit))" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "flat.fold(best_fit).plot(alpha=0.4);" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.6" } }, "nbformat": 4, "nbformat_minor": 2 }